CN112819195B - A fine-grained prediction method for tunnel advance drilling geology - Google Patents

Abstract

A geological fine forecasting method for tunnel advanced drilling, which utilizes energy theory to forecast the geological of the unknown stratum of the tunnel, firstly collects the original drilling data of a multifunctional drilling machine, including drilling parameters of the multifunctional drilling machine, on-site liquid return and slag discharge, and the surrounding rock condition record of the tunnel face, then processing the original drilling data of the multifunctional drilling machine, including removing abnormal drilling parameters and interpolating at the position of the connecting rod, roughly partitioning the rock stratum according to the records of liquid return and slag discharge, then calculating RTPR value based on energy theory and data statistical index thereof by utilizing the preprocessed drilling parameters, establishing the corresponding relation between the RTPR statistical index and the surrounding rock engineering property, finally establishing a forecast reference plane according to the tunnel face condition, and (4) predicting unknown stratum distribution and surrounding rock lithology through the known condition of the tunnel face, and synthesizing rough zoning conditions to obtain a final prediction result. The method can effectively utilize drilling site data and realize advanced drilling and fine forecasting of the tunnel.

Description

A fine-grained prediction method for tunnel advance drilling geology

technical field

The invention relates to the field of tunnel geological survey, in particular to a method and application for fine-grained forecasting of tunnel advance drilling geology.

Background technique

At present, the types of tunnels built in China have grown to large scales, and the forecast of many unforeseen complex and unfavorable geological bodies, such as karst, water and mud inrush, and gas, has always been a major difficulty in tunnel geological forecasting. The advanced drilling method is currently the most direct and effective geological detection method for predicting complex and unfavorable geological bodies in tunnels. At present, it can carry out medium and long-distance (0-150m) detection, and can accurately and intuitively reflect the surrounding rock geological conditions around the borehole. At present, the accuracy of the advanced drilling forecast results depends on the interpretation of drilling parameters and the situation of backflow and slag discharge, which requires high forecasting experience for the interpreters. The results are generally limited to the division of the soft and hard degree of the surrounding rock or to roughly judge the development degree of the surrounding rock fissures according to the uneven oscillation of the drilling parameters. The fundamental reason is that the simultaneous analysis of multiple drilling parameters is not only inefficient but also unable to accurately predict. The detailed characteristics of the unknown formation lead to a waste of a large amount of useful drilling parameter response information, and the misjudgment rate is extremely high. Therefore, obtaining maximum drilling parameter response information and efficient and rapid geological prediction are the difficult problems that need to be solved in drilling geological prediction. On the basis of the existing advanced drilling forecasting technology, it is of great significance to ensure the safety of tunnel construction by making use of the drilling data that can be collected at the drilling site to the maximum extent to make precise forecasts for the unknown formation of the tunnel.

SUMMARY OF THE INVENTION

In order to overcome the above-mentioned deficiencies of the prior art, the present invention provides a method and application for fine prediction of tunnel advance drilling geology, which can efficiently utilize on-site drilling data to perform fine prediction on unknown strata of the tunnel.

The technical scheme adopted in the present invention is: a method and application for fine prediction of tunnel advance drilling geology, by preprocessing original drilling data, calculating the rotary thrust power ratio RTPR and its statistic, and selecting a reference section to predict unknown strata Make refined forecasts, including the following steps:

(1) Collect the original drilling data of the multi-functional drilling rig, including drilling parameters, liquid return and slag discharge records, connecting rod position, face conditions and drilling layout records;

(2) Preprocessing the original data, including removing and interpolating the drilling parameters of abnormal connecting rod positions, and roughly partitioning the rock formations according to the liquid return and slag discharge records, and obtaining the rough division results of the rock formations;

(3) Calculate the RTPR value based on energy theory and its data statistical index using the preprocessed drilling parameters, and establish the corresponding relationship between the RTPR statistical index and surrounding rock engineering properties, where RTPR is the ratio of drilling rotational power and propulsion power , the data statistical indicators of RTPR include: mean, standard deviation, rate of change, mean and standard deviation of the rate of change;

The specific calculation formula of the RTPR value based on the energy theory is:

P = T ₁ ·ω=T ₁ ·( _2πn )

P _push = F ₁ ·V ₁ ≈T ₂ ·A·V ₁

In the formula: T ₁ is the measured torque of the drill pipe; ω is the rotational angular velocity of the drill bit; n is the measured rotational speed of the drill bit. F ₁ is the measured propulsion force corresponding to the pressure exerted on the drill pipe; V ₁ is the drilling speed of the drill bit; T ₂ is the propulsive pressure actually exerted by the drill bit on the rock; A is the cross-sectional area of the drill pipe. Described RTPR index is the ratio of P _movement and P _push ;

(4) Establish the forecast reference section, select the relatively stable section of RTPR curve statistics from the face as the response to the known surrounding rock conditions on the face, and use this as the forecast reference section. Realize the prediction of the surrounding rock lithology of the unknown strata in the whole section, and obtain the prediction results of the engineering properties of the surrounding rock;

(5) Based on the rough division results of rock formations and the prediction results of surrounding rock engineering properties, the drilling depth scale is further divided into different surrounding rock intervals to form a fine division of surrounding rock conditions within the drilling depth range and output the results.

The specific steps for removing and interpolating the abnormal data of the docking rod position are: first, according to the input coordinate position of the post point, divide the range of 20cm before and after the post point as an interval where abnormal data may occur, and the parameters in the interval are greater than 3 times or The data points less than 1/3 of the mean of the normal value are eliminated, and then the two nearest points of the elimination point are taken, the average value is calculated, and it is inserted into the elimination position.

The specific corresponding relationship between the RTPR statistic and the engineering properties of surrounding rock is as follows: RTPR mean value describes the average value of segment data, that is, the average hardness of surrounding rock; The variation trend of hardness, the standard deviation value of RTPR index describes the development degree of joints and fissures in the surrounding rock, and the standard deviation of the RTPR change rate describes the integrity of the surrounding rock.

The concrete steps of establishing the forecast reference section are: selecting RTPR curve sections within a certain interval range in the RTPR mean and standard deviation in the statistics in the section from the starting point, and the selection principle needs to be satisfied: when the curve is generally stable, the standard When the overall curve shows an upward or downward trend, a relatively stable section should be selected, and the standard deviation should be used as the main factor for secondary selection in this section, and the corresponding surrounding rock evaluation will respond according to statistics , to increase or decrease the grade relative to the surrounding rock on the face; when the curve has no relatively stable section, a linear section should be selected as much as possible, the linear regression value should be used instead of the mean to calculate the standard deviation of this section, and the secondary selection should be made based on this. , the corresponding surrounding rock evaluation is based on the mean value of the statistic of the reference section, and the level of the surrounding rock on the face is increased or decreased. The length of the reference section should meet 1/2 to 1/5 of the rod length, and the selected end point should not exceed the first rod change. 20cm before the location.

The above-mentioned comprehensive rock formation rough division results and surrounding rock engineering property prediction results, and the specific steps for further dividing the borehole depth scale into different surrounding rock intervals are as follows: when the liquid return and slag discharge can be successfully obtained in the whole section, each complete area is obtained. According to the rough division of the interval, and combined with the lithology prediction results of the surrounding rock engineering, the final result of the refined prediction can be obtained; when the liquid return and slag discharge in the section cannot be obtained smoothly, the range of RTPR statistics is calibrated according to the available liquid return and slag discharge. The prediction is made in the uncertain area, and the final result of the refined prediction is obtained in combination with the lithology prediction results of the surrounding rock engineering.

Compared with the prior art, the present invention has the beneficial effects that the effective signal response information of the drilling parameters can be fully extracted, and the surrounding rock can be predicted finely, and the realization process is more efficient and convenient.

Description of drawings

Fig. 1: the implementation flow of the present invention;

Figure 2: The tunnel face of No. 2 tunnel in the lower row, (a) the tunnel face of the left hole, (b) the tunnel face of the right hole;

Figure 3: Drilling layout;

Figure 4: RTPR curve of hole #1 on the left line.

Detailed ways

The technical solutions of the present invention will be further described below with reference to the accompanying drawings and embodiments. The examples are only used to explain the present invention, and are not intended to limit the scope of the present invention.

The C6-XP fully hydraulic crawler-type multi-function drilling rig developed by the Italian company Casa Quorandi was used to conduct advance drilling detection on the No. When the left hole of the tunnel was excavated to the face ZK373+090 and the right hole was excavated to the face YK373+060, the karst cave filled with clay mixed with boulders was exposed respectively. No obvious water seepage was found in the karst cave, and local collapse occurred during the construction process. Collapsing karst cavity. The drilling method used in this drilling is top drive hydraulic hammer type. The drilling parameters are collected by the LUTZ drilling data acquisition system mounted on the drilling rig. The main drilling parameters include: drilling speed, torque, rotation speed and propulsion pressure, and at the drilling site, the color of the returned liquid during the drilling process is recorded. and slag discharge. Table 1 and Figure 1 show the layout of the advanced horizontal drilling holes in the No. 2 tunnel in the lower row.

To process the collected drilling data, take the 1# hole on the left line and the 7# hole on the right line as examples, and proceed as follows:

(1) Collect the original drilling data of the multi-functional drilling rig, including: the records of liquid return and slag discharge, the position of the connecting rod, the condition of the face and the drilling arrangement records. Table 1 shows the layout of the advanced horizontal drilling holes in the No. 2 tunnel in the lower row.

Table 1 Drilling hole arrangement for advance horizontal drilling of No. 2 tunnel in the lower row

(2) Eliminate and interpolate the drilling parameters with abnormal positions of the drilling parameters, and roughly partition the rock formations according to the liquid return and slag discharge records, and obtain the rough division results of the rock formations. Table 2 shows the rough zoning results of the rock formation obtained from the 7# hole on the right line according to the slag discharge and liquid return.

Table 2 The rough zoning results of the rock formation in the #7 hole on the right line of the No. 2 tunnel in the lower row

(3) Using the preprocessed drilling parameter base to calculate the RTPR value based on energy theory and its statistical indicators. Figure 3 is the RTPR curve of hole 1# in the left line obtained by calculation.

(4) Establish the forecast reference section, select the relatively stable section of RTPR curve statistics from the face as the response to the known surrounding rock conditions on the face, and use this as the forecast reference section. The prediction of the surrounding rock lithology of the unknown strata in the whole section can be realized, and the prediction results of the engineering properties of the surrounding rock can be obtained. Taking the limestone area of the 1# hole on the left line as an example, 16-17m is selected as the benchmark section, and the corresponding surrounding rock evaluation is shown in Table 3. The corresponding surrounding rock engineering property evaluation is shown in Table 4;

Table 3 Statistics and evaluation of surrounding rock

Table 4. Evaluation of engineering properties of surrounding rock in the limestone area of the 1# hole on the left line

(5) Based on the rough division results of rock formations and the prediction results of surrounding rock engineering properties, for the uncertain sections where the liquid return and slag discharge cannot be obtained smoothly, the range of RTPR statistics is calibrated according to the available liquid return and slag discharge conditions. Make predictions. The drilling depth scale is further divided into different surrounding rock intervals to form a fine division of surrounding rock conditions within the drilling depth range. Table 5 shows the rough division of the 1# hole on the left line and the comparison between the comprehensive surrounding rock engineering property prediction and the actual excavation.

Table 5 Rough division of comprehensive surrounding rock engineering property forecast and comparison of actual excavation

It can be seen from Table 5 that the final forecast result obtained by the method of the present invention is basically consistent with the actual excavation situation, which proves that the method of the present invention is reasonable and effective.

The above descriptions are only preferred embodiments of the present invention, and do not impose any limitations on the present invention. Any simple modifications, changes and equivalent structural changes made to the embodiments according to the present invention still fall within the protection scope of the technical solutions of the present invention. .

Claims (3)

1. a kind of tunnel advance drilling geological refinement prediction method, it is characterized in that, by carrying out preprocessing to original drilling data, calculate the rotary thrust power ratio RTPR and its statistic, select the reference section to carry out refinement prediction to unknown strata, Include the following steps: (1) Collect the original drilling data of the multi-functional drilling rig, including drilling parameters, liquid return and slag discharge records, connecting rod position, face conditions and drilling layout records; (2) Preprocessing the original data, including removing and interpolating the drilling parameters of abnormal connecting rod positions, and roughly partitioning the rock formations according to the liquid return and slag discharge records, and obtaining the rough division results of the rock formations; (3) Calculate the RTPR value based on energy theory and its data statistical index using the preprocessed drilling parameters, and establish the corresponding relationship between the RTPR statistical index and surrounding rock engineering properties, where RTPR is the ratio of drilling rotational power and propulsion power , the data statistical indicators of RTPR include: mean, standard deviation, rate of change, mean and standard deviation of the rate of change; The specific calculation formula of the RTPR value based on the energy theory is: P = T ₁ ·ω=T ₁ ·( _2πn ) P _push = F ₁ ·V ₁ ≈T ₂ ·A·V ₁ In the formula: T ₁ is the measured torque of the drill pipe; ω is the rotational angular velocity of the drill bit; n is the measured rotational speed of the drill bit; F ₁ is the measured propulsion force corresponding to the pressure exerted on the drill pipe; V ₁ is the drilling speed of the drill bit; T ₂ is the drill bit The propulsion pressure actually applied to the rock; A is the cross-sectional area of the drill pipe, and the RTPR index is the ratio of P _dynamic to P _thrust ; The specific corresponding relationship between the RTPR statistic and the engineering properties of surrounding rock is as follows: RTPR mean value describes the average value of segment data, that is, the average hardness of surrounding rock; The change trend of hardness, the standard deviation of RTPR index describes the development degree of joints and fissures in the surrounding rock, and the standard deviation of the RTPR change rate describes the integrity of the surrounding rock; (4) Establish the forecast reference section, select the relatively stable section of RTPR curve statistics from the face as the response to the known surrounding rock conditions on the face, and use this as the forecast reference section. Realize the prediction of the surrounding rock lithology of the unknown strata in the whole section, and obtain the prediction results of the engineering properties of the surrounding rock; The concrete steps of establishing the forecast reference section are: selecting RTPR curve sections within a certain interval range in the RTPR mean and standard deviation in the statistics in the section from the starting point, and the selection principle needs to be satisfied: when the curve is generally stable, the standard When the overall curve shows an upward or downward trend, a relatively stable section should be selected, and the standard deviation should be used as the main factor for secondary selection in this section, and the corresponding surrounding rock evaluation will respond according to statistics , to increase or decrease the grade relative to the surrounding rock on the face; when the curve has no relatively stable section, a linear section should be selected as much as possible, the linear regression value should be used instead of the mean to calculate the standard deviation of this section, and the secondary selection should be made based on this. , the corresponding surrounding rock evaluation is based on the mean value of the statistic of the reference section, and the level of the surrounding rock on the face is increased or decreased. The length of the reference section should meet 1/2 to 1/5 of the rod length, and the selected end point should not exceed the first rod change. 20cm before the position; (5) Based on the rough division results of rock formations and the prediction results of surrounding rock engineering properties, the drilling depth scale is further divided into different surrounding rock intervals to form a fine division of surrounding rock conditions within the drilling depth range and output the results. 2. The method for fine-grained prediction of tunnel advanced drilling geology according to claim 1, wherein the concrete steps of removing and interpolating the abnormal data of the connecting rod position are: at first, divide the connecting rod point according to the input coordinate position of the connecting rod point. The range of 20 cm before and after is the interval that may cause abnormal data. Data points with parameters greater than 3 times or less than 1/3 of the mean value of the normal value in this interval are excluded, and then the two nearest points of the excluded point are taken, the average value is calculated, and it is inserted into the excluded position. 3. The method for fine-grained prediction of tunnel advanced drilling geology according to claim 1, characterized in that, said comprehensive rock formation is roughly divided into results and surrounding rock engineering property prediction results, and the drilling depth scale is further divided into different surrounding rock intervals. The specific steps are: when the liquid return and slag discharge can be successfully obtained in the whole section, obtain each complete rough division interval, and combine with the lithology prediction results of surrounding rock engineering to obtain the final result of fine prediction; When the slag cannot be obtained smoothly, the RTPR statistic range is calibrated according to the available backflow and slag discharge situation, and the uncertain area is predicted, and the final result of refined prediction is obtained in combination with the lithology prediction results of surrounding rock engineering.

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